Machine Learning Engineer IV

What you'll do

• Design and deploy content understanding, semantic matching, retrieval, and multi-objective ranking models for multimodal content.
• Build representation learning systems using LLMs, vision-language models, and embedding models to improve content relevance.
• Develop scalable retrieval and ranking systems to power search, recommendations, and agentic workflows across Adobe products.
• Train, fine-tune, and optimize machine learning models using large-scale behavioral, content, and synthetic datasets.
• Create evaluation frameworks and benchmarks to measure ranking quality, retrieval effectiveness, and user impact.
• Manage the full ML systems lifecycle including data preparation, model development, deployment, monitoring, and continuous improvement.
• Translate innovative research from Adobe Research into production-ready capabilities for various engineering teams.

What we're looking for

• Experience building and deploying machine learning systems in production.
• Experience with retrieval, recommendation, ranking, search relevance, or semantic matching systems.
• Working knowledge of modern ML techniques including representation learning, transformer architectures, and multi-objective optimization.
• Experience working with LLMs, embedding models, vision-language models, or other multimodal foundation models.
• Strong software engineering skills with proficiency in Python and experience with ML services and infrastructure.
• Proficiency with modern ML frameworks such as PyTorch, TensorFlow, JAX, Hugging Face, Ray, or Spark.
• Experience designing and analyzing offline and online evaluations, including A/B testing and relevance metrics.
• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field, or equivalent experience.